Currently Viewing:
The American Journal of Managed Care December 2019
Clinical Characteristics and Treatment Patterns Among US Patients With HIV
Julie L. Priest, MSPH; Tanya Burton, PhD; Cori Blauer-Peterson, MPH; Kate Andrade, MPH; and Alan Oglesby, MPH
Partnering in Postacute Darkness? CMS Has Data That Will Help
Terry E. Hill, MD
From the Editorial Board: Anne K. Gauthier, MS
Anne K. Gauthier, MS
Preventive/Office Visit Patient Knowledge and Their Insurance Information Gathering Perceptions
Evan K. Perrault, PhD; Katie J. Schmitz, BA; Grace M. Hildenbrand, MA; and Seth P. McCullock, MA
Cost-Sharing Payments for Out-of-Network Care in Commercially Insured Adults
Wendy Yi Xu, PhD; Bryan E. Dowd, PhD; Macarius M. Donneyong, PhD; Yiting Li, PhD; and Sheldon M. Retchin, MD, MSPH
Benzodiazepine and Unhealthy Alcohol Use Among Adult Outpatients
Matthew E. Hirschtritt, MD, MPH; Vanessa A. Palzes, MPH; Andrea H. Kline-Simon, MS; Kurt Kroenke, MD; Cynthia I. Campbell, PhD, MPH; and Stacy A. Sterling, DrPH, MSW
Catheter Management After Benign Transurethral Prostate Surgery: RAND/UCLA Appropriateness Criteria
Ted A. Skolarus, MD, MPH; Casey A. Dauw, MD; Karen E. Fowler, MPH; Jason D. Mann, MSA; Steven J. Bernstein, MD, MPH; and Jennifer Meddings, MD, MS
A Claims-Based Algorithm to Reduce Relapse and Cost in Schizophrenia
Heidi C. Waters, PhD, MBA; Charles Ruetsch, PhD; and Joseph Tkacz, MS
Cost Burden of Hepatitis C Virus Treatment in Commercially Insured Patients
Christine Y. Lu, PhD; Dennis Ross-Degnan, ScD; Fang Zhang, PhD; Robert LeCates, MA; Caitlin Lupton, MSc; Michael Sherman, MD; and Anita Wagner, PharmD
Currently Reading
Delivery System Performance as Financial Risk Varies
Joseph P. Newhouse, PhD; Mary Price, MA; John Hsu, MD, MBA; Bruce Landon, MD, MBA; and J. Michael McWilliams, MD, PhD
Outcome Measures for Oncology Alternative Payment Models: Practical Considerations and Recommendations
Jakub P. Hlávka, PhD; Pei-Jung Lin, PhD; and Peter J. Neumann, ScD

Delivery System Performance as Financial Risk Varies

Joseph P. Newhouse, PhD; Mary Price, MA; John Hsu, MD, MBA; Bruce Landon, MD, MBA; and J. Michael McWilliams, MD, PhD
One delivery system’s healthcare utilization in its Medicare Advantage product was notably less than in its Pioneer accountable care organization or in a traditional Medicare comparison group.
ABSTRACT

Objectives: Banner Health, a large delivery system in Maricopa County, Arizona, entered into both Medicare and commercial insurance contracts that varied the amount of financial risk that Banner assumed. Rates of utilization and spending under these various contracts were investigated.

Study Design: Prior to 2012, Banner held Medicare Advantage (MA) contracts, and in 2012 it began as a Medicare Pioneer accountable care organization (ACO). Banner also introduced a commercial ACO contract in that year. We compared risk-adjusted healthcare utilization and spending in the MA plan, the ACO, and a local traditional Medicare (TM) comparison group. We also compared risk-adjusted utilization and spending in Banner’s commercial ACO with that of a comparison group drawn from the same employment groups who were not attributed to Banner providers.

Methods: We used claims and encounter data to measure utilization and spending. We risk adjusted using CMS and HHS Hierarchical Condition Categories.

Results: Within Medicare, MA enrollees had lower risk-adjusted utilization and total spending than either the Pioneer ACO participants or a local TM comparison group. Participation in the Pioneer ACO program was associated with a greater reduction in hospitalization rates for ACO patients relative to local TM patients served by non-ACO providers, but the effect on total medical spending was ambiguous. Risk-adjusted differences between the commercial ACO group and the fee-for-service comparison group were generally small.

Conclusions: The results are consistent with CMS’ efforts to shift reimbursement away from pure fee-for-service reimbursement.

Am J Manag Care. 2019;25(12):e388-e394
Takeaway Points

We assessed the performance of a large delivery system, Banner Health, that takes risk under a Medicare Advantage (MA) plan, a Medicare accountable care organization (ACO), and a commercial ACO.
  • Within Medicare, risk-adjusted healthcare utilization was less in Banner’s MA plan than in its Pioneer ACO and in a traditional Medicare comparison group.
  • Its ACO program had a larger fall in hospitalization rates than a traditional Medicare comparison group.
  • Spending effects in its commercial ACO were modest, perhaps because of churn.
  • These results support CMS’ efforts to shift reimbursement away from traditional fee-for-service.
Value-based purchasing has emphasized moving away from pure fee-for-service reimbursement by shifting some financial risk from insurers to healthcare delivery systems and provider groups. One of the highest-profile efforts has been accountable care organizations (ACOs), which share financial risk with payers for a defined population of patients rather than being paid solely on a fee-for-service basis for an undefined population. Successful ACOs could contemplate assuming full financial risk—for example, by becoming Medicare Advantage (MA) plans or entering into capitation (percent of premium or delegated risk) contracts with existing MA or commercial insurance plans.

Evaluation of ACO performance to date has largely focused on individuals in Medicare ACOs, comparing their healthcare utilization with that of individuals in traditional Medicare (TM) who are not in ACOs.1-4 These evaluations have found modestly lower spending and unchanged or modestly higher quality at ACOs, with savings growing over time and with effects concentrated in physician- rather than hospital-based entities. Evaluation of a commercial ACO-like contract found a similar result.5

In this paper, we broaden the focus by comparing a Medicare ACO not only with a TM comparison group but also with an MA plan within the same delivery system. In addition, we compare utilization and cost in the same organization’s commercial ACO with a commercially insured comparison group. Because the organization shared risk in its MA plan over our entire period of observation, we expected that utilization and spending in the MA plan would initially be below that of the ACO group, in which accepting risk began during the observation period. After the establishment of the Medicare and commercial ACOs, we expected their utilization to decrease more rapidly than that of comparison groups.

METHODS

Banner Health and Its Insurance Contracts

Our data came from 1 large delivery system, Banner Health, which is headquartered in Phoenix, Arizona (Maricopa County). Banner operates in several sites in the western United States, but we limited our sample to residents of Maricopa County, where the great majority of Banner users live. Not only was Banner one of the original participants in the Medicare Pioneer ACO program that began in 2012, but for several years before 2012, it partnered with Blue Cross Blue Shield of Arizona (BCBS Arizona) to offer an MA plan. Banner’s contractual incentives in the MA plan were complex, but risk was shared approximately equally between BCBS Arizona and Banner. In its Pioneer ACO, Banner chose a Core Option B contract, which meant it accepted 70% 2-sided risk in year 1 and 75% 2-sided risk in years 2 and 3, with both upside and downside risk capped at 10% of total spending.

Also starting in 2012, Banner partnered with Aetna to offer a commercial ACO product to larger self-insured employers (those with >50 employees) that had an existing preferred provider organization (PPO) contract. Similar to Medicare’s ACO attribution rules, employees of the participating firms and their dependents were prospectively attributed to a Banner primary care physician (PCP) if they used a Banner PCP for the plurality of evaluation and management (E&M) services in the prior year. Providers of those not attributed were reimbursed at negotiated fee-for-service rates. Similar to the Medicare program, Banner shared financial risk for the attributed participants for all medical services against a benchmark. Employee benefits were the same for all employees and dependents in the PPO contract. In addition to its Pioneer ACO and Medicare Advantage plan, Banner had other risk-based arrangements, such that about 30% of its revenue was risk-based.

Banner’s performance in the Pioneer ACO program depended on the method of assessment. CMS’ formal evaluation for years 1 and 2 used a difference-in-differences (DID) model with 2 TM control groups: 1 from the local (“near”) market and 1 from a nonlocal (“far”) market—with the latter group to account for potential spillovers in the local market. The question that the CMS evaluation sought to answer was whether the ACO’s spending growth was less than either comparison group’s. On this criterion, Banner did not save money in years 1 and 2.6

CMS’ method for rewarding Pioneer ACOs, however, differed from its evaluation method and was based on a benchmark, which was a function of the historical spending of attributed beneficiaries at the ACO trended forward at a national trend rate. Using this method of assessment, Banner performed well (eAppendix [available at ajmc.com]).

Data

Medicare. The data for the ACO and TM comparison groups come from the 100% Medicare files for Maricopa County for 2010 to 2014. All parts A and B spending are included; drug spending was omitted, other than injected or infused drugs covered under Part B. MA data come from BCBS Arizona. The MA covered services analyzed here are the same as the TM services. The MA dollar figures use allowed charges, which are based on contracted unit prices that are confidential. These unit prices are not identical to TM prices, so some of the difference in spending between the MA group and the other 2 groups arises from unit price differences.

An alternative to using the contracted charges is to impute Medicare unit prices based on procedure and site-of-service codes. Although this would hold unit price constant in spending comparisons, it is a laborious and potentially error-prone procedure; we thus rejected it because BCBS Arizona asserted that its prices closely approximated TM prices, consistent with findings nationally and consistent with having a competitive MA product.7 Because of the close approximation between the contracted unit prices and TM prices, the proportion of spending differences between the MA group and the other 2 groups that is attributable to unit price differences should be small.


 
Copyright AJMC 2006-2020 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
x
Welcome the the new and improved AJMC.com, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up